Symposium for dental treatment of medically complex children: Practice based culminating experience a continuing education course

The purpose of this Continuing Education Course is to provide oral health professionals with information to address the unique dental needs of medically complex children. The objective is to train dentists to treat special needs patients so these children have more access to oral healthcare. ^ Under the auspice of Dell Children Hospital of Austin, Lisa Jacob DDS MS is administering this Continuing Education Course for dentists and dental staff from the 46 counties of central Texas served by the hospital.^ Needs assessment was determined through a survey questionnaire to collect data about the number of special needs patients seen by general dentists in Central Texas.^ In recent years, an increasing number of continuing education courses have been developed to help dentists learn techniques for providing dentistry in more understanding ways to patients with special needs. Dentists and dental staff are trained to provide care specifically in dentistry, regardless of who the patient is. This means dentists can perform a clinical examination, carry out procedures to diagnose and treat oral diseases, and provide restorations such as fillings and crowns. ^ Four prominent speakers will provide an instructional tool to address the need for dentists to increase their competence and comfort level in caring for individuals with developmental disabilities. Each speaker will address one of the most frequently encountered cases of medically complex children. The four topics selected by Dr. Lisa Jacob are Cancer, Mental Disability, Downs Syndrome, and Craniofacial Syndromes.^ The public health implications of this continuing education course are presented in providing dental service to this underserved population. When general dentist turn away patients with special needs because of lack of knowledge to treat them, these patients will, more than likely, postpone or abandon needed dental visits because of difficulties reaching pediatric dentists who may not be available in certain areas.^

Recommendations for dementia caregiver stress interventions based on Intervention Mapping guidelines

Stress can affect a person's psychological and physical health and cause a variety of conditions including depression, immune system changes, and hypertension (Alzheimer's Association, 2010; Aschbacher et al., 2009; Fredman et al., 2010; Long et al., 2004; Mills et al., 2009; von Känel et al., 2008). The severity and consequences of these conditions can vary based on the duration, amount, and sources of stress experienced by the individual (Black & Hyer, 2010; Coen et al., 1997; Conde-Sala et al., 2010; Pinquart & Sörensen, 2007). Caregivers of people with dementia have an elevated risk for stress and its related health problems because they experience more negative interactions with, and provide more emotional support for, their care recipients than other caregivers. ^ This paper uses a systematic program planning process of Intervention Mapping to organize evidence from literature, qualitative research and theory to develop recommendations for a theory- and evidence-based intervention to improve outcomes for caregivers of people with dementia. A needs assessment was conducted to identify specific dementia caregiver stress influences and a logic model of dementia caregiver stress was developed using the PRECEDE Model. Necessary behavior and environmental outcomes are identified for dementia caregiver stress reduction and performance objectives for each were combined with selected determinants to produce change objectives. Planning matrices were then designed to inform effective theory-based methods and practical applications for recommended intervention delivery. Recommendations for program components, their scope and sequence, the completed program materials, and the program protocols are delineated along with ways to insure that the program is adopted and implemented after it is shown to be effective.^

Semantic Technology Recommendation Based on the Analytic Network Process

Semantic technologies have become widely adopted in recent years, and choosing the right technologies for the problems that users face is often a difficult task. This paper presents an application of the Analytic Network Process for the recommendation of semantic technologies, which is based on a quality model for semantic technologies. Instead of relying on expert-based comparisons of alternatives, the comparisons in our framework depend on real evaluation results. Furthermore, the recommendations in our framework derive from user quality requirements, which leads to better recommendations tailored to users’ needs. This paper also presents an algorithm for pairwise comparisons, which is based on user quality requirements and evaluation results.

A knowledge-based method for generating summaries of spatial movement in geographic areas

In this article we describe a method for automatically generating text summaries of data corresponding to traces of spatial movement in geographical areas. The method can help humans to understand large data streams, such as the amounts of GPS data recorded by a variety of sensors in mobile phones, cars, etc. We describe the knowledge representations we designed for our method and the main components of our method for generating the summaries: a discourse planner, an abstraction module and a text generator. We also present evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.

Impact of knowledge brokering on performance heterogeneity among business models

Purpose – The strategic management literature lacks a comprehensive explanation as to why seemingly similar business models in the same industry perform differently. This paper strives to explain this phenomenon. Design/methodology/approach – The model is conceptualized and accompanied by a case study on the airline industry to explain knowledge brokerage that creates value from the effective utilization of knowledge resources acquired from intra- and inter-firm environments. Findings – The model explains a cyclical view of business model flexibility in which the knowledge-based resource accumulation of the business model is spread across the intra- and inter-firm environments. Knowledge brokerage strategies from the inter- and intra-firm environments result in improved performance of the business model. The flexibility that the business model acquires is determined by how efficiently resource accumulation is aligned with its external environment. Originality/value – The paper effectively integrates the concepts of knowledge brokerage and business models from a resource accumulation-based view and simultaneously arrives at the performance heterogeneity of seemingly similar business models within the same industry. It has performance implications for firms that start out without any distinct resources of their own, or that use an imitated business model, to attain better performance through business model evolution aligned with successful knowledge brokerage strategies. It adds to the resource accumulation literature by explaining how resources can be effectively acquired to create value.

Models for Internal Quality Fruit Sorting, Based on Time- Domain Laser Reflectance Spectroscopy (TDRS)

Time domain laser reflectance spectroscopy (TDRS) was applied for the first time to evaluate internal fruit quality. This technique, known in medicine-related knowledge areas, has not been used before in agricultural or food research. It allows the simultaneous non-destructive measuring of two optical characteristics of the tissues: light scattering and absorption. Models to measure firmness, sugar & acid contents in kiwifruit, tomato, apple, peach, nectarine and other fruits were built using sequential statistical techniques: principal component analysis, multiple stepwise linear regression, clustering and discriminant analysis. Consistent correlations were established between the two parameters measured with TDRS, i.e. absorption & transport scattering coefficients, with chemical constituents (sugars and acids) and firmness, respectively. Classification models were built to sort fruits into three quality grades, according to their firmness, soluble solids and acidity.

HF spectrum activity prediction model based on HMM for cognitive radio applications

Although most of the research on Cognitive Radio is focused on communication bands above the HF upper limit (30 MHz), Cognitive Radio principles can also be applied to HF communications to make use of the extremely scarce spectrum more efficiently. In this work we consider legacy users as primary users since these users transmit without resorting to any smart procedure, and our stations using the HFDVL (HF Data+Voice Link) architecture as secondary users. Our goal is to enhance an efficient use of the HF band by detecting the presence of uncoordinated primary users and avoiding collisions with them while transmitting in different HF channels using our broad-band HF transceiver. A model of the primary user activity dynamics in the HF band is developed in this work to make short-term predictions of the sojourn time of a primary user in the band and avoid collisions. It is based on Hidden Markov Models (HMM) which are a powerful tool for modelling stochastic random processes and are trained with real measurements of the 14 MHz band. By using the proposed HMM based model, the prediction model achieves an average 10.3% prediction error rate with one minute-long channel knowledge but it can be reduced when this knowledge is extended: with the previous 8 min knowledge, an average 5.8% prediction error rate is achieved. These results suggest that the resulting activity model for the HF band could actually be used to predict primary users activity and included in a future HF cognitive radio based station.

Olfactory fMRI Connectivity Analysis Based on Granger Causality with Application in Anosmia Assessment

In this work, we describe hubs organization within the olfactory network with Functional Magnetic Resonance Imaging (fMRI). Granger causality analyses were applied in the supposed regions of interest (ROIs) involved in olfactory tasks, as described in [1]. We aim to get deeper knowledge about the hierarchy of the regions within the olfactory network and to describe which of these regions, in terms of strength of the connectivity, impair in different types of anosmia.

Implementation of wireless communication based on Software Defined Radio

In current communication systems, there are many new challenges like various competitive standards, the scarcity of frequency resource, etc., especially the development of personal wireless communication systems result the new system update faster than ever before, the conventional hardware-based wireless communication system is difficult to adapt to this situation. The emergence of SDR enabled the third revolution of wireless communication which from hardware to software and build a flexible, reliable, upgradable, reusable, reconfigurable and low cost platform. The Universal Software Radio Peripheral (USRP) products are commonly used with the GNU Radio software suite to create complex SDR systems. GNU Radio is a toolkit where digital signal processing blocks are written in C++, and connected to each other with Python. This makes it easy to develop more sophisticated signal processing systems, because many blocks already written by others and you can quickly put them together to create a complete system. Although the main function of GNU Radio is not be a simulator, but if there is no RF hardware components,it supports to researching the signal processing algorithm based on pre-stored and generated data by signal generator. This thesis introduced SDR platform from hardware (USRP) and software(GNU Radio), as well as some basic modulation techniques in wireless communication system. Based on the examples provided by GNU Radio, carried out some related experiments, for example GSM scanning and FM radio station receiving on USRP. And make a certain degree of improvement based on the experience of some investigators to observe OFDM spectrum and simulate real-time video transmission. GNU Radio combine with USRP hardware proved to be a valuable lab platform for implementing complex radio system prototypes in a short time. RESUMEN. Software Defined Radio (SDR) es una tecnología emergente que está creando un impacto revolucionario en la tecnología de radio convencional. Un buen ejemplo de radio software son los sistemas de código abierto llamados GNU Radio que emplean un kit de herramientas de desarrollo de software libre. En este trabajo se ha empleado un kit de desarrollo comercial (Ettus Research) que consiste en un módulo de procesado de señal y un hardaware sencillo. El módulo emplea un software de desarrollo basado en Linux sobre el que se pueden implementar aplicaciones de radio software muy variadas. El hardware de desarrollo consta de un microprocesador de propósito general, un dispositivo programable (FPGA) y un interfaz de radiofrecuencia que cubre de 50 a 2200MHz. Este hardware se conecta al PC por medio de un interfaz USB de 8Mb/s de velocidad. Sobre la plataforma de Ettus se pueden ejecutar aplicaciones GNU radio que utilizan principalmente lenguaje de programación Python para implementarse. Sin embargo, su módulo de procesado de señal está construido en C + + y emplea un microprocesador con aritmética de coma flotante. Por lo tanto, los desarrolladores pueden rápida y fácilmente construir aplicaciones en tiempo real sistemas de comunicación inalámbrica de alta capacidad. Aunque su función principal no es ser un simulador, si no puesto que hay componentes de hardware RF, Radio GNU sirve de apoyo a la investigación del algoritmo de procesado de señales basado en pre-almacenados y generados por los datos del generador de señal. En este trabajo fin de máster se ha evaluado la plataforma de hardware de DEG (USRP) y el software (GNU Radio). Para ello se han empleado algunas técnicas de modulación básicas en el sistema de comunicación inalámbrica. A partir de los ejemplos proporcionados por GNU Radio, hemos realizado algunos experimentos relacionados, por ejemplo, escaneado del espectro, demodulación de señales de FM empleando siempre el hardware de USRP. Una vez evaluadas aplicaciones sencillas se ha pasado a realizar un cierto grado de mejora y optimización de aplicaciones complejas descritas en la literatura. Se han empleado aplicaciones como la que consiste en la generación de un espectro de OFDM y la simulación y transmisión de señales de vídeo en tiempo real. Con estos resultados se está ahora en disposición de abordar la elaboración de aplicaciones complejas.

The impact of sustainable construction and knowledge management on sustainability goals. A review of the venezuelan renewable energy sector

The recognition of the relevance of energy, especially of the renewable energies generated by the sun, water, wind, tides, modern biomass or thermal is growing significantly in the global society based on the possibility it has to improve societies′ quality of life, to support poverty reduction and sustainable development. Renewable energy, and mainly the energy generated by large hydropower generation projects that supply most of the renewable energy consumed by developing countries, requires many technical, legal, financial and social complex processes sustained by innovations and valuable knowledge. Besides these efforts, renewable energy requires a solid infrastructure to generate and distribute the energy resources needed to solve the basic needs of society. This demands a proper construction performance to deliver the energy projects planned according to specifications and respecting environmental and social concerns, which implies the observance of sustainable construction guidelines. But construction projects are complex and demanding and frequently face time and cost overruns that may cause negative impacts on the initial planning and thus on society. The renewable energy issue and the large renewable energy power generation and distribution projects are particularly significant for developing countries and for Latin America in particular, as this region concentrates an important hydropower potential and installed capacity. Using as references the performance of Venezuelan large hydropower generation projects and the Guri dam construction, this research evaluates the tight relationship existing between sustainable construction and knowledge management and their impact to achieve sustainability goals. The knowledge management processes are proposed as a basic strategy to allow learning from successes and failures obtained in previous projects and transform the enhancement opportunites into actions to improve the performance of the renewable energy power generation and distribution projects.

A knowledge based framework to support active aging at home based environments

Information and Communication Technologies can support Active Aging strategies in a scenario like the Smart Home. This paper details a person centered distributed framework, called TALISMAN+, whose aim is to promote personal autonomy by taking advantage of knowledge based technologies, sensors networks, mobile devices and internet. The proposed solution can support an elderly person to keep living alone at his house without being obliged to move to a residential center. The framework is composed by five subsystems: a reasoning module that is able to take local decisions at home in order to support active aging, a biomedical variables telemonitorisation platform running on a mobile device, a hybrid reasoning middleware aimed to assess cardiovascular risk in a remote way, a private vision based sensor subsystem, and a secure telematics solution that guarantees confidentiality for personal information. TALISMAN+ framework deployment is being evaluated at a real environment like the Accessible Digital Home.

Automatic 3DTV Quality Assessment Based On Depth Perception Analysis

Quality assessment is a key factor for stereoscopic 3D video content as some observers are affected by visual discomfort in the eye when viewing 3D video, especially when combining positive and negative parallax with fast motion. In this paper, we propose techniques to assess objective quality related to motion and depth maps, which facilitate depth perception analysis. Subjective tests were carried out in order to understand the source of the problem. Motion is an important feature affecting 3D experience but also often the cause of visual discomfort. The automatic algorithm developed tries to quantify the impact on viewer experience when common cases of discomfort occur, such as high-motion sequences, scene changes with abrupt parallax changes, or complete absence of stereoscopy, with a goal of preventing the viewer from having a bad stereoscopic experience.

Brain injury MRI simulator based on theoretical models of neuroanatomic damage

In order to improve the body of knowledge about brain injury impairment is essential to develop image database with different types of injuries. This paper proposes a new methodology to model three types of brain injury: stroke, tumor and traumatic brain injury; and implements a system to navigate among simulated MRI studies. These studies can be used on research studies, to validate new processing methods and as an educational tool, to show different types of brain injury and how they affect to neuroanatomic structures.

Monitoring visual attention on a neurorehabilitation environment based on interactive video

The use of new technologies in neurorehabilitation has led to higher intensity rehabilitation processes, extending therapies in an economically sustainable way. Interactive Video (IV) technology allows therapists to work with virtual environments that reproduce real situations. In this way, patients deal with Activities of the Daily Living (ADL) immersed within enhanced environments [1]. These rehabilitation exercises, which focus in re-learning lost functions, will try to modulate the neural plasticity processes [2]. This research presents a system where a neurorehabilitation IV-based environment has been integrated with an eye-tracker device in order to monitor and to interact using visual attention. While patients are interacting with the neurorehabilitation environment, their visual behavior is closely related with their cognitive state, which in turn mirrors the brain damage condition suffered by them [3] [4]. Patients’ gaze data can provide knowledge on their attention focus and their cognitive state, as well as on the validity of the rehabilitation tasks proposed [5].

Supervised classification of minimally invasive surgery psychomotor competence based on instruments motion analysis

Background Objective assessment of psychomotor skills has become an important challenge in the training of minimally invasive surgical (MIS) techniques. Currently, no gold standard defining surgical competence exists for classifying residents according to their surgical skills. Supervised classification has been proposed as a means for objectively establishing competence thresholds in psychomotor skills evaluation. This report presents a study comparing three classification methods for establishing their validity in a set of tasks for basic skills’ assessment. Methods Linear discriminant analysis (LDA), support vector machines (SVM), and adaptive neuro-fuzzy inference systems (ANFIS) were used. A total of 42 participants, divided into an experienced group (4 expert surgeons and 14 residents with >10 laparoscopic surgeries performed) and a nonexperienced group (16 students and 8 residents with <10 laparoscopic surgeries performed), performed three box trainer tasks validated for assessment of MIS psychomotor skills. Instrument movements were captured using the TrEndo tracking system, and nine motion analysis parameters (MAPs) were analyzed. The performance of the classifiers was measured by leave-one-out cross-validation using the scores obtained by the participants. Results The mean accuracy performances of the classifiers were 71 % (LDA), 78.2 % (SVM), and 71.7 % (ANFIS). No statistically significant differences in the performance were identified between the classifiers. Conclusions The three proposed classifiers showed good performance in the discrimination of skills, especially when information from all MAPs and tasks combined were considered. A correlation between the surgeons’ previous experience and their execution of the tasks could be ascertained from results. However, misclassifications across all the classifiers could imply the existence of other factors influencing psychomotor competence.